Measuring Embodiment: Movement Complexity and the Impact of Personal Characteristics
Measuring Embodiment: Movement Complexity and the Impact of Personal Characteristics
复制标题
衡量体现：运动复杂性和个人特征的影响
DOI：
10.1109/tvcg.2023.3270725
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发表时间：
2023
影响因子：
5.2
通讯作者：
Good, Jessica J.
中科院分区：
文献类型：
--
作者：
Peck, Tabitha C.;Good, Jessica J.
用户的个人体验和特征可能会影响化身错觉的强度，并以未知的方式影响由此产生的行为变化。本文采用结构方程模型对两个完全身临其境的用户研究(n=189和n=99)进行了重新分析，以检验个人特征对主观体现的影响。结果表明，个体特征(性别、对科学、技术、工程或数学的参与-实验1、年龄、电子游戏经验-实验2)预测了不同的自我报告的具身体验结果也表明，自我报告的具体化增加预测了环境反应，在这种情况下，虚拟环境中的反应更快、更准确。重要的是，头部跟踪数据被证明是预测具体化的有效客观措施，而不需要研究人员使用额外的设备。
A user's personal experiences and characteristics may impact the strength of an embodiment illusion and affect resulting behavioral changes in unknown ways. This paper presents a novel re-analysis of two fully-immersive embodiment user-studies (n = 189 and n = 99) using structural equation modeling, to test the effects of personal characteristics on subjective embodiment. Results demonstrate that individual characteristics (gender, participation in science, technology, engineering or math – Experiment 1, age, video gaming experience – Experiment 2) predicted differing self-reported experiences of embodiment Results also indicate that increased self-reported embodiment predicts environmental response, in this case faster and more accurate responses within the virtual environment. Importantly, head-tracking data is shown to be an effective objective measure for predicting embodiment, without requiring researchers to utilize additional equipment.